Workflow =>
- 读取CSV文件并获取单价列数据
- 转换列数据价格并创建名为'Fabric'的新列
- 将输出保存为xlsx 示例:
Unit Price
----------
330
350
380
I want to convert this data
Fabric
------
Card
Combed
Viscos
我代码:
##Fabric Data
getFabric = df_new['Unit Price']
result = []
for fabric in getFabric:
if fabric == 310:
result.append("Card")
elif fabric == 330:
result.append("Combed Dawah")
elif fabric == 350:
result.append("Combed Regular")
elif fabric == 490:
result.append("Viscos")
elif fabric == 550:
result.append("Pleated")
else:
result.append(fabric)
df_new['Fabric'] = result
错误:
这很简单，老兄…
your_df["Fabric"] = your_df["Unit Price"].apply(lambda x: str(x).replace("330", "Card"))
# do this for every conversion
your_df.to_csv("filename.csv")
以上代码可以保存为CSV文件，可以在MS EXCEL中查看
而不是迭代列值。试试这个,
pandas内置函数称为.replace()，用于替换列中的值而无需迭代
df_new['Unit Price'].replace({310: 'Card', 330: 'Combed Dawah', 350: 'Combed Regular', 490: 'Viscos', 550: 'Pleated'}, inplace=True)